Searcharxiv⌕ Search

arXiv · 2610.25018

Structure-Aware Equivalence for Evaluating Autoformalized Statements

Abstract

Evaluating autoformalized mathematical statements requires determining whether a candidate preserves the mathematical claim intended by a trusted reference. Existing methods approach this problem from complementary directions: reference-free learned evaluators estimate semantic agreement but are not constrained to a formal equivalence relation, while reference-based proof methods typically employ whole-statement logical equivalence to provide formal certificates, which is too coarse for translation fidelity and may identify mathematically unrelated statements. We introduce Structure-Aware Equivalence (SAE), a role-preserving formal equivalence relation between syntactic and whole-statement logical equivalence that allows formally justified reformulations while preserving translation-relevant mathematical structure. We operationalize SAE in the Autoformalization Correctness Evaluator (ACE), which provides certified equivalence or inequivalence judgments and reports Inconclusive otherwise. On ProofNetVerif, a benchmark introduced with BEq+, ACE retains substantial equivalent-case coverage while remaining highly conservative in certifying disputed or inequivalent pairs. On targeted diagnostics, BEq+ accepts 94-96% of unrelated but whole-statement logically equivalent pairs, while Mathesis LeanScorer accepts 42% of localized meaning-changing perturbations; ACE accepts none of either set as equivalent.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yi Yu, Yu-Hsuan Wu, Guang Lin, Yuhui Zhang, Yuxiang Peng. 2026-10-18. Structure-Aware Equivalence for Evaluating Autoformalized Statements. https://arxiv.org/abs/2610.25018

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Foundational Refinement Proofs for EVM Bytecode, at the Price of Tokens

Relating executable code to a high-level model of its behavior has been a central concern of programming-language research for decades. Formally verified compilers, translation validators and certifying compilers address this problem through different trade-offs between proof effort, automation, generality, and the size of the trusted base. Recently, large language models (LLMs) have begun to change the economics of formal verification. Agentic proof development is now capable of producing machine-checked proofs, sometimes unsupervised, at a scale and speed that were previously out of reach. We propose a verification architecture that takes advantage of this shift. An executable obtains a machine-checked proof that it behaves according to a high-level model, independently of the compiler that produced it. The proof is written by an LLM agent. We evaluate the feasibility of this architecture for the Ethereum Virtual Machine (EVM). We build EquiVM, a foundational framework in Lean comprising an executable EVM semantics and a formal specification language, Stele, that gives a high-level authoritative model of the bytecode's behavior, but commits to no source language or compilation toolchain. We state what it means for EVM bytecode to refine a Stele spec and we build a proof library to facilitate proof construction. We evaluate the capabilities of frontier LLMs to construct such proofs, as well as the cost of proof production and repair. Our results show that agents prove 35 real production contracts end to end, without modifying their source or bytecode, among them core contracts of Safe, Morpho, Compound and Uniswap protocols, with bytecode of size close to the maximum the EVM allows. Several proofs need only the initial prompt, the rest a handful of human inputs, and existing proofs are repaired in a fraction of the original time when the source or the compiler configuration changes.

cs.PL↗

Noise-aware Verification and Synthesis of Quantum Programs

This work provides a comprehensive framework for noise-aware quantum program analysis, ranging from logical foundations to model checking and automated synthesis. While most research on quantum programming considers an idealized, noise-free semantics for quantum programs, we reason about quantum programs that are executed on real, noisy hardware. We use the error models published by quantum-hardware vendors to give a hardware-dependent semantics to quantum programs. We then present a noise-aware quantum Hoare logic with a relatively complete proof system. We finally use state-space exploration techniques for the hardware-aware verification and synthesis of loop-free quantum programs. In this way, we synthesize optimal, hardware-dependent solutions for parity bit-flip, GHZ state preparation, and other problems that commonly occur as subroutines in larger quantum algorithms. We evaluate our method on all 55 hardware specifications provided by the IBM Qiskit toolkit. Finally, we also show that classical probabilistic branching is needed for optimality in quantum programming.

cs.PL↗

Record Types Everywhere

This paper introduces a novel calculus that models first-class environments and function application paradigms using standard record types. By proposing new extensions to general record types, we achieve a design that is remarkably simple and principled. We formalise this design in a core calculus and prove several desirable properties, including type soundness, normalization, and a simulation of the simply typed lambda calculus. Additionally, we extend the design with mutable references. The calculus, its semantics, along with the extension, and all stated properties are fully mechanized in the Lean 4 proof assistant, alongside an interpreter formally verified to be equivalent to the operational semantics.

cs.PL↗